Tag

ASPIRE: Agentic /Skills Discovery for Robotics

Autonomously generates, iteratively debugs, and composes robot control programs into a reusable skill library for discovering and refining manipulation skills across simulation and real robots. Uses a code-as-policy continual learning loop—accumulating validated sensorimotor skills instead of model weights—to tackle long-horizon household and benchmark tasks.

Gen-HumanEgo

Provides 1,800+ hours of synchronized egocentric multi-view recordings with 3D hand reconstructions, wide‑FOV depth, and hierarchical task/subtask annotations for embodied AI and robot learning. Includes six fisheye views, hand meshes, and per-episode temporal labels across 44k+ episodes.

TacVerse: A Multi-scene Bimanual Visuo-Tactile Dataset

Provides synchronized visual and tactile demonstrations for bimanual manipulation, with four fingertip tactile streams recorded on every frame. Collected using handheld grippers rather than robot execution, it supports research on contact-rich imitation learning and multimodal perception.

HOI-Retarget — Humanoid Human–Object Interaction Motion

Generates humanoid robot motion references that preserve object contact locations/timing by solving windowed trajectory optimizations against contact targets in the object frame. Releases retargeted trajectories for two Unitree robots across 75 objects (≈13.9k robot–motion pairs); CC BY‑NC‑SA 4.0.

Imagined Data

Provides imagined interaction segments generated by world models for RoboTwin2.0 tasks, stored as fixed-length HDF5 chunks (21 observation frames, 20 actions, rewards and episode flags). Useful for training and evaluating world-model-based policies; currently limited to the RoboTwin2.0 subdataset.

InternW0-$Δ$: A World Action Model Bridging Predictive Dynamics and Actions with 20K+ Hours of Open Data

Learns joint predictive visual dynamics and action generation for generalist robot manipulation, translating future-relevant visual representations into actions. Integrates a Mixture-of-Transformers coupling a video expert and action expert, a frozen vision-language model for semantics, 4D distillation, and Causal Imprint; pretrained on a 20K+ hour heterogeneous corpus.

Agent Priors-guided Policy Learning

Records structural priors with skill-specific policies so a runtime agent can select and compose the version of each skill best suited to new states, improving out-of-distribution and compositional generalization for robot manipulation from few demonstrations.

SharpaDex v1.0

Multimodal real-robot dataset of 28,993 teleoperated bimanual manipulation demonstrations (~300 hours) with synchronized multi-view RGB/tactile videos, 65D robot state/action, 60D fingertip tactile signals, and temporally aligned language segments; intended for imitation, visuomotor and visual‑tactile research, CC BY‑NC 4.0 (non‑commercial).

MotorMind: Scaffolding General Vision Language Models for Zero-Shot Robot Manipulation

Lets general-purpose vision-language models directly command robots via a compact mid-level action interface and asynchronous monitoring, enabling zero-shot manipulation without task-specific policy training; demonstrates strong sim benchmarks and real xArm6 transfer.

FineART: Fine-Grained Annotated Robotic Trajectory Dataset

Provides fine-grained language labels across complete bimanual robot trajectories, enabling step-by-step policy learning from 40,543 demonstrations and 533,913 human-written subtasks.

Has GPT-6-Astra Achieved Embodied Intelligence?

Evaluates GPT-6-Astra as an embodied policy across 12 robotic benchmarks, examining in‑context learning, hybrid System‑2/System‑1 control, and real‑world deployment gaps; finds strong benchmark competence but practical limits from demonstration cost, latency, and failure recovery.

HexaShell: A Thin Harness for Exploring the Limits of VLM Agents as Robot Coding Agents

Turns a VLM into a robot-coding agent that directly drives a dual-arm robot from three RGB cameras, iteratively writing and fixing small executable perception and control tools from observations and logs; evaluated on 42 RoboDojo tasks.